How many hours a day do you spend scrolling on your phone or computer? The internet keeps track of these tabs, whether you’re learning, working, shopping, or just catching up with friends. But do you know this information plays a direct role in your search for companionship online?
Understanding Big Data and Its Relevance to Online Dating
Generally, big data is a term that refers to massive amounts of data that’s ever growing, and it would be impossible to process it using traditional data-processing software.
What an app does with this kind of information is what truly matters. Analyzing data from a source allows an app to:
- Improve efficiencies in operations
- Optimize the development of a product
- Increase growth opportunities and drive new revenue.
On the other hand, dating apps that pair big data with high-performance analytics allow for more impressive feats:
- Spot anomalies faster and more accurately
- Determine root causes of defects, failures, and issues
- Sharpen algorithms to accurately react to changing variables
- Detect fraudulent behavior on an app.
Does Your Data Footprint Affect the Quality of Matches?
Basically, online dating data comprises the information you fill out on a dating app. This includes your likes and interests, passions, physical features, political stance, behavior, age, income, and so forth. However, most users are not honest when answering such prompts, thus creating a huge weakness in the system. So how do dating apps deal with dishonest people looking for genuine connections?
Online dating giants such as Tinder, Match.com, or Bumble tend to collect their big data analytics from Facebook, social media profiles, and shopping websites. This type of information has proven to be more helpful in predicting human behavior.
However, there is more than meets the eye regarding matching algorithms on dating apps. How does a dating app apply big data and machine learning to pair individuals? Technically, this will vary depending on the app and the type of matches it has to offer:
- Location-based services – Most dating apps are location-centered, suggesting matches to a given proximity. This makes it more convenient for users seeking something more casual or those who are constantly traveling.
- Compatibility-focused dating apps – On the other hand, there are several online dating platforms that offer a more immersive experience. The matches on such sites are based on qualitative data such as life goals, values, and shared interests.
Dating apps, such as Match.com and eHarmony, are more popular than most free dating apps, which leads us to believe that people care about the quality of prospective partners. Such online dating platforms also work to prevent swipe burnout for their users.
To understand just how influential and important big data is to online dating, Facebook is looking to launch a dating platform. The founder and CEO, Mark Zuckerberg, recently announced that Facebook will be an algorithm-based app that works towards creating real and long-term relationships.
Great! Now we have a basic understanding of big data and how it affects our social and romantic experiences. But how exactly does it work?
How Dating Apps Apply Big Data to Online Dating
Here are some of the most prominent methods by which existing dating sites and apps analyze big data for efficient matchmaking.
Multiple Data Sources Equals Richer Dating Profiles
Normally, a dating app will ask you to complete a personality questionnaire at sign-up. The length and depth of these questionnaires will vary depending on the dating app, with some being hundreds of questions long. This personal information is critical and valuable, but it’s not all that apps use.
By granting permissions to your dating app, it can gain additional data insight from the other sites you use, such as streaming sites, social media platforms, online shopping sites, and more. This information gives more details about an individual and helps to balance out the lies you put on your profile. Pretty smart, right?
Using a feature known as collaborative filtering, users are matched based on shows they watch and stuff they buy online. If we’re being honest, this offers a more harmonious result compared to questionnaire data alone.
Deep Learning Enables Facial Recognition in Online Dating
When it comes to online dating, personality alone isn’t going to cut it. That is why most apps allow users to match with individuals who match their physical preferences.
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Machine learning and deep learning are types of AI with the aim of mimicking human behavior. Machine learning AI will automatically adapt with the least amount of human interference. Conversely, deep learning uses artificial neural networks to mimic how the human brain works.
With deep learning, a dating app is able to identify specific facial features by analyzing huge data of human images. Since this AI trains itself, it can identify a face’s main characteristics that differentiate it from other individuals.
Analyzing User Behavior Helps to Identify the Kind of Partner You Really Want
You might not be actively aware of it, but there is a disconnect between what people say they want while setting up a profile and the types of profiles they mostly interact with. The matching algorithm is meant to read between the lines and adapt to your change in preferences.
Thanks to questionnaire data, consumer information from third parties, and AI, your dating app will start recommending match suggestions based on profiles where you spend the most time, not just what you specified at sign-up. So, if you think you prefer power-hungry businessmen but can’t stay away from free-spirited artists, the dating app will guide you home.
Another dating app that’s winning the big data game is eHarmony. The sites examine how users interact with the site, how often they log in, and how much time they spend online. Such information is used to judge how invested they are in finding a partner. In addition, the site analyses historical data from past matches. The use of AI helps identify successful and actionable insights that would increase the app’s efficiency.
Fraud Detection
The biggest risk on any dating app would be getting scammed. Who is on the other side of the screen, and do they genuinely want to connect with you?
While it might be impossible to tell, dating apps are getting more apt at detecting fishy accounts. By pairing the user’s behavior data with machine learning, an app should be able to suspect any suspicious activities on the app. Deep learning can identify suspicious activities, such as copy-pasting messages, and detect conversations about private information and finances.
Dating apps are getting safer and friendlier, and it’s all thanks to big data.
Conclusion
Matchmaking is a process that has been passed through thousands of generations, and the internet has revolutionized the experience. Big data is an important tool that helps identify a user’s likes and interests. It is natural to idealize yourself when looking for a partner, but that tends to mess with what you’d really want. Big data knows you better than you do, so why not sit back and let it find you the ideal partner?
Are you currently using a dating app? What are some of the experiences that make it a great dating app?